1. Field of the Invention
One or more embodiments of the invention are related to fantasy league systems. More particularly, but not by way of limitation, at least one embodiment of the invention compares or otherwise combines at least one user's fantasy teams in at least one league with the additional user's fantasy teams, applies a weighting to one or more players if a weighting exists, and displays an aggregate view of the combination based on the weighting with a player favorability view for fantasy league players. The weighting may be based on the user's desire to beat another user in a particular league, based on the ratio of the amount of money spent to enter each league or based on any other item, ratio, function, event or anything parameter. The aggregate view may include a fine-grained display such as lists of players that are “for”, i.e., only playing on fantasy teams for the at least one user, and playing on more teams for the at least one user than for the additional users and hence are favorable to the at least one user, and playing on an equal number of the at least one user's and additional user's teams and that are neutral to the at least one user, and playing on less teams for the at least one user than for the additional users and hence are unfavorable to the at least one user and only on the additional user's fantasy teams and hence are against the at least one user. Other embodiments may display a coarse-grained list of for/against or other subset or grouping of the fine-grained display for example. Embodiments thus enable a user to determine whether a current player performance should be cheered for or not at that moment, or is helping or hurting the overall fantasy performance of the user based on the related fantasy ownership of the players with respect to additional users or standings in the fantasy league so that a user may have favorability towards players that are not playing for the user if the players would help the user's standing in one or more fantasy leagues, for example if a lower standing user was to win against a higher ranking user other than a first user. For favorable and unfavorable players, the system may calculate a range of scores for one or more players that enables the user to support a player that may help the user in certain leagues and hurt the user in other leagues, wherein the range allows the user to advance in the most leagues or based on weighting of the leagues or players. Thus embodiments of the invention enable the first user to cheer or otherwise support a player that may hurt the standing of the first user in at least one league, but improve the standing of the first user in at least one league, for example a league that the first user has not made the playoffs yet in.
2. Description of the Related Art
Generally, fantasy leagues are common. There are many types of fantasy leagues that enable users to compete by picking players and forming teams related to sports, games, notoriety and many other characteristics. For example, sports fantasy leagues involve sports such as football, baseball, soccer, hockey, golf, cricket, auto racing, surfing, etc., and allow users to pick players to form their own team to compete against other users based on player performances, statistics, scores or a myriad of other types of values including simple head to head matchups. Game fantasy leagues involve games such as poker, blackjack, etc., and enable users to pick players to form their own team and compete against other users. Celebrity fantasy leagues enable users to pick a group of celebrities wherein scores are related to the number of pictures of celebrities that appear in various magazines.
Many sports fans are involved in multiple fantasy leagues for various sports. Current fantasy systems are generally standalone systems that do not provide information related to more than one league that a specific player is involved with in a meaningful or helpful manner. For example, there are no known systems that provide a display that informs a user whether to cheer or not if a specific player scores since that player may be on more opposing fantasy teams in various leagues that the user is involved with and that ratio of for/against can change every week. Hence, if a particular player scores a touchdown in a given game, a user may be informed to cheer since the user has the player on more fantasy teams that other players. However, if the same player scores again in a different game at a later date, other users may have drafted or traded for the player, meaning that the user should not cheer for the player at that later date since a touchdown from the player is hurting the user's fantasy league performance overall as the user owns the player less than other users over multiple leagues.
Known systems for sports fantasy leagues, accessible via mobile computers and/or web-applications, typically use algorithms and computations to help a user determine best player picks for a specific fantasy league. In addition, existing systems may display trade recommendations in one or more leagues using information associated with the values of one or more players. The values of one or more players are typically computed using statistical methods such as a player position, period of time, points, etc., and using projected statistics to rank players from best to worst for a given fantasy league. These systems are generally involved with the problem of obtaining or maintaining team rosters based on player performance, but they are incapable of displaying relative value of a player's performance with respect to a first user versus additional user's since the player may be on several fantasy teams associated with the first user as well as several fantasy teams associated with additional users in multiple leagues that the first user is in. Hence, these systems cannot readily determine if the first user is relatively benefiting from a player performance or not, for example if a particular player scores a touchdown, existing systems are unable to notify a user whether to cheer or not based on the various overall leagues that the user is in with respect to that player's ownership by other users in multiple leagues.
For example, United States Patent Publication 20120329541 to Allen et al., entitled “Fantasy Sports Neural Engine and Method of Using Same”, discloses a neural engine that sums all leagues and determine best player pick using algorithms, computations, etc., to best simulate human reasoning, and pattern recognition. The network appears to be accessible and used on PCs, mobile phones, etc., and used for any recreational activity/sport. The system also appears to use historical performance information for at least two fantasy sports teams in at least two fantasy sports leagues, wherein the at least two leagues are associated with one sports draft; to arrive at a recommendation. The system also appears to use a trade comparator for trade recommendations in one or more leagues in one draft, and information regarding the values of the players in the leagues.
It appears as though the system of Allen et al. recognizes that a user in one league will participate in the same league for years, or multiple users in one league will play together in a different league, therefore all players' histories are stored and projected across all leagues for all years. In other words, all player statistics across multiple leagues are accessible by the neural engine to provide a better projection on what each player on each team is likely to do once drafted. Also, one member (user) appears to have access to all player statistics in the multiple leagues the member (user) is associated with, to assess player projections and tendencies across multiple leagues.
In addition, the neural engine of Allen et al. is capable of averaging, for example using a weighted average, of all statistical lists and projections across multiple leagues and teams to assess a likely good draft list of players. The neural engine appears to suggest tendencies, favorite players, favorite teams, and favorite positions of other teams in the league, including an opposing user's history. The engine suggests that the list provided may be used by an opposing member, and suggests a different pick. For example, the engine may provide prediction percentages of the chance an opposing member will choose a running back, wide receiver, etc. on an American Football fantasy league. In summary this system appears to be directed at the initial pick or trading of players and not displaying how the players are favorable versus other user's players, for example during a game. Hence, there is no way to know whether to celebrate a player's performance or not since although a user may have a particular player in multiple leagues, other users of varying numbers may also have the player.
The drawbacks of using such a neural engine is that the neural engine does not appear to use data accumulation to present a single interface showing player favorability from aggregated data. In addition, the engine does not appear to weight the players' and teams statistics to a user's (member) points, in order to determine favorability, without the need to include an opposing member's league data. Although the engine is capable of aggregating data across multiple leagues, for a single user, the engine does not appear to provide statistical recommendations as to whether a specific player from a specific team will hurt or help a specific user (member), based on the single user's points/history. For example, the engine may provide prediction percentages of the chance an opposing member will choose or draft a running back, wide receiver, etc., but not in regards to a specific player, of a specific position on a specific team, and not with respect to whether the player's current performance is beneficial to the first user or not based on the number of other user's which have already drafted the player in the multiple leagues the first user has a fantasy team in.
United States Patent Publication 20110237317 to Nooran et al., entitled “Apparatus and Method for Recommending Roster Moves In Fantasy Sports Teams”, discloses a roster modification recommendation system for fantasy sports leagues. The system appears to use projected statistics on one or more players, on one team or several teams. The system mentions various statistical methods, such as position, period of time, etc, for recommending trade or acquisition to the user. The system is able to accumulate statistics (for a game, week, month, etc) and compare those to similar statistics of other fantasy teams in one league, or many leagues. For example, the system allows users to communicate with a server (web, app, etc) to get information on players and teams in one or more fantasy leagues owned by the same user. The system also appears to use statistics to determine scoring, project player statistics for specific players, using point projections in a specific league. The system may also compute demand for a player, using movement of players in other leagues, and provide a recommendation to the user.
While the system appears to disclose the use of multiple leagues for a single user, and accumulating data from the multiple leagues, the system does not specifically state whether the recommendations are based on a user's current and/or past history points for a specific player, and does not specifically aggregate data on a single player on a single interface, by stating whether a specific player is favored or “unfavored”, associated with the user's historical moves, data, points, etc. The system is more geared towards comparisons of other leagues, to recommend a move on a single league, rather than a specific player, and for example does not indicate whether a particular performance by a particular player is something worth cheering about, or otherwise indicating whether the performance hurts or helps the user based on all of the leagues that the user has fantasy teams in.
United States Patent Publication 20110230243 to Hereford et al., entitled “Fantasy Sports Engine for Recommending Optimum Team Rosters”, appears to disclose the use of multiple leagues and recommends whether a user should add/drop/trade players based on computations, for each league. However, the system of Hereford et al., does not appear to view statistics, history, etc., of each player across multiple leagues at once.
United States Patent Publication 20130045805 to Penning et al., entitle “Fantasy Sports Leagues Comprising Historical Players and/or Historical Results”, appears to use multiple leagues in one application/server, however does not appear to provide recommendations using data aggregation across leagues for the same user, or indications as to whether a particular player's performance helps or hurts the overall fantasy league performance of a user having multiple fantasy teams in multiple leagues wherein the player may be on multiple other user's fantasy teams.
United States Patent Publication 20120270614 to Robinson et al., entitled “Method for Playing Fantasy Sports”, appears to disclose a system that uses multiple teams/leagues and multiple players, and ranks all players across teams/leagues, individually. However, the system does not appear to aggregate players across leagues for a single user.
United States Patent Publication 20090082111 to Smith et al., entitled “System and Method for Connecting Users Based on Common Interests, Such As Shared Interests of Representations of Professional Athletes” appears to disclose a system connected to various sites, and aggregates data from the multiple sites. However, it appears that the multiple sites are not necessarily associated with the user's leagues and points, but rather other users' data/league information.
United States Patent Publication 200800268951 to Gropp et al., entitled “Data Visualization System for Fantasy Sporting Events”, appears to disclose a system that views and compares statistics of various players, teams and leagues using a single interface, and ranks players from overall statistics. However, the system does not appear to provide an interface to the user for ranking or otherwise displaying the players in terms of overall favorability, “unfavorability”, etc. over the user's points, with respect to whether the player is on more, less or equal number of other user's fantasy teams for example.
In summary, there are no known systems that utilize a fantasy league weighted aggregation system to use data accumulation to present a single interface showing player favorability from aggregated data, and weight the players' and teams statistics to a user's points, in order to determine favorability, without the need to include an opposing member's league data. In addition, there are no known system that are capable of aggregating data across at least one league, for a first user or with respect to other users having a standing in at least one league and provide statistical recommendations as to whether a specific player from a specific team is hurting or helping the first user, based on the first user's points/history, in regards to a specific player, of a specific position on a specific team or a match up against other users in a particular league other than the first user. With the popularity of fantasy sports leagues, a fan may be involved in several leagues, making it difficult to know if a specific player within each league is currently helping or hurting the first user's overall fantasy teams in at least one league for example. In addition, there are no known fantasy systems that enable favorability ratings to be calculated and/or displayed for users other than the first user and shown to the first user so that the first use may cheer for a player not on the first user's fantasy team if the player's performance would help the first user, e.g., allow a higher standing user to be defeated by a lower standing user, which would help the first user improve the first user's standing in a fantasy league. There are no known systems that enable weighting of a player based on the first user's desire to beat another user or win a particular league or based on the ratio of entry fees for the fantasy leagues or in any other manner to alter the favorability of a particular player, even if the player is not on the first user's fantasy team, wherein the player may actually help the first user move up in standings. There are no known systems that calculate a range of scores for one or more players to enable a user to support a player that may help the user in certain leagues and hurt the user in other leagues, wherein the range allows the user to advance in the most leagues. Hence there is a need for a fantasy league weighted aggregation system that presents a combined view of all the user's sports fantasy leagues and organizes the leagues in a manner allowing a user to determine whether a specific player is all for, favorable, neutral, unfavorable or all against at least one user versus additional user's fantasy teams.